Import stock prices
stocks <- tq_get(c("AAPL", "NFLX", "AMZN"),
get = "stock.prices",
from = "2016-01-01")
stocks
## # A tibble: 5,823 × 8
## symbol date open high low close volume adjusted
## <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 AAPL 2016-01-04 25.7 26.3 25.5 26.3 270597600 24.0
## 2 AAPL 2016-01-05 26.4 26.5 25.6 25.7 223164000 23.4
## 3 AAPL 2016-01-06 25.1 25.6 25.0 25.2 273829600 22.9
## 4 AAPL 2016-01-07 24.7 25.0 24.1 24.1 324377600 22.0
## 5 AAPL 2016-01-08 24.6 24.8 24.2 24.2 283192000 22.1
## 6 AAPL 2016-01-11 24.7 24.8 24.3 24.6 198957600 22.5
## 7 AAPL 2016-01-12 25.1 25.2 24.7 25.0 196616800 22.8
## 8 AAPL 2016-01-13 25.1 25.3 24.3 24.3 249758400 22.2
## 9 AAPL 2016-01-14 24.5 25.1 23.9 24.9 252680400 22.7
## 10 AAPL 2016-01-15 24.0 24.4 23.8 24.3 319335600 22.1
## # ℹ 5,813 more rows
Plot stock prices
stocks %>%
ggplot(aes(x = date, y = adjusted, color = symbol)) +
geom_line()
Filter rows
stocks %>% filter(adjusted > 24)
## # A tibble: 5,708 × 8
## symbol date open high low close volume adjusted
## <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 AAPL 2016-01-04 25.7 26.3 25.5 26.3 270597600 24.0
## 2 AAPL 2016-03-16 26.2 26.6 26.1 26.5 153214000 24.3
## 3 AAPL 2016-03-17 26.4 26.6 26.2 26.5 137682800 24.2
## 4 AAPL 2016-03-18 26.6 26.6 26.3 26.5 176820800 24.3
## 5 AAPL 2016-03-21 26.5 26.9 26.3 26.5 142010800 24.3
## 6 AAPL 2016-03-22 26.3 26.8 26.3 26.7 129777600 24.5
## 7 AAPL 2016-03-23 26.6 26.8 26.5 26.5 102814000 24.3
## 8 AAPL 2016-03-24 26.4 26.6 26.2 26.4 104532000 24.2
## 9 AAPL 2016-03-28 26.5 26.5 26.3 26.3 77645600 24.1
## 10 AAPL 2016-03-29 26.2 26.9 26.2 26.9 124760400 24.7
## # ℹ 5,698 more rows
Arrange rows
stocks %>% arrange(adjusted > 24)
## # A tibble: 5,823 × 8
## symbol date open high low close volume adjusted
## <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 AAPL 2016-01-05 26.4 26.5 25.6 25.7 223164000 23.4
## 2 AAPL 2016-01-06 25.1 25.6 25.0 25.2 273829600 22.9
## 3 AAPL 2016-01-07 24.7 25.0 24.1 24.1 324377600 22.0
## 4 AAPL 2016-01-08 24.6 24.8 24.2 24.2 283192000 22.1
## 5 AAPL 2016-01-11 24.7 24.8 24.3 24.6 198957600 22.5
## 6 AAPL 2016-01-12 25.1 25.2 24.7 25.0 196616800 22.8
## 7 AAPL 2016-01-13 25.1 25.3 24.3 24.3 249758400 22.2
## 8 AAPL 2016-01-14 24.5 25.1 23.9 24.9 252680400 22.7
## 9 AAPL 2016-01-15 24.0 24.4 23.8 24.3 319335600 22.1
## 10 AAPL 2016-01-19 24.6 24.7 23.9 24.2 212350800 22.0
## # ℹ 5,813 more rows